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Predictive Factors for Delayed Recovery From Anesthesia in Patients Receiving Free Vascularized Flap Reconstruction for Head and Neck Defects: A Retrospective Cohort Study.
Zeng, Meigu; Wu, Jiayao; Liu, Xiongying; Xiao, Xiliang; Cao, Minghui; Wang, Chengli.
Afiliação
  • Zeng M; Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou.
  • Wu J; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene, Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University.
  • Liu X; Department of Anesthesiology, Guangdong Women and Children Hospital, PR China.
  • Xiao X; Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou.
  • Cao M; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene, Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University.
  • Wang C; Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou.
J Craniofac Surg ; 2024 Jul 08.
Article em En | MEDLINE | ID: mdl-38975723
ABSTRACT

OBJECTIVE:

Free flap reconstruction for head and neck defects is currently a common procedure. This study aimed to create and validate a predictive model for identifying patients at risk of delayed recovery from anesthesia after free flap reconstruction for head and neck defect.

METHODS:

Electronic medical records from all patients were retrospectively collected. The primary outcome variable was delayed recovery from anesthesia. The least absolute shrinkage and selection operator regression model was employed to identify the most relevant features, followed by the construction of a nomogram model using multivariable logistic regression analysis. The discriminatory power, calibration, and clinical utility of the nomogram model were assessed using receiver operating characteristic curve analysis, calibration curve analysis, and decision curve analysis, respectively.

RESULTS:

This novel nomogram model incorporated 4 predictors for delayed recovery from anesthesia preoperative albumin, intraoperative fresh frozen plasma infusion, preoperative platelet-to-lymphocyte ratio, and duration of intraoperative hypotension. The area under the receiver operating characteristic curve (area under the curve) for the nomogram model was determined to be 0.821 (95% CI 0.803-0.836). After internal validation, the corrected area under the curve was found to be 0.768 (95% CI 0.639-0.812). In addition, the model exhibited well-fitted calibration curves and demonstrated favorable clinical usability as indicated by the calibration curve and decision curve analysis curve.

CONCLUSION:

The authors created and validated a novel predictive model utilizing a limited number of 4 predictors, yet exhibiting commendable predictive performance. This innovative tool holds the potential to mitigate delayed recovery from anesthesia and enhance the efficient allocation of medical resources.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article